Mian Usman Sattar | Artificial Intelligence | Best Researcher Award

Dr. Mian Usman Sattar | Artificial Intelligence | Best Researcher Award

University of Derby | United Kingdom

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Early Academic Pursuits

Dr. Mian Usman Sattar’s academic journey reflects a sustained commitment to excellence in computing, informatics, and information systems. He began with a Postgraduate Diploma in Communication and Computer Technology from Government College University, Lahore (2002), followed by an M.Sc. in Computer Science (2004). His pursuit of international exposure led him to the United Kingdom, where he earned a Postgraduate Diploma in Computer Science (2008) and an MS in IT Management from the University of Sunderland (2010). His academic trajectory culminated in a Ph.D. in Informatics from the Malaysian University of Science and Technology (2022), under the guidance of Prof. Dr. Ang Ling Weay. Currently, he is further enhancing his expertise through a PG Certificate leading to FHEA from the University of Derby, UK (expected 2025).

Professional Endeavors

Dr. Sattar’s career spans academia, industry, and research leadership. His current role as Lecturer and Program Leader (Information Technology) at the University of Derby involves teaching diverse modules such as IT Product Design, Web Technologies, and Analytics Ethics. Prior to this, he served as Assistant Professor of Business Intelligence at Beaconhouse National University (2020–2023), where he introduced contemporary courses in analytics and emerging technologies. His earlier tenure as Assistant Professor of Information Systems at the University of Management and Technology (2014–2020) saw him direct academic programs, establish industry collaborations, and lead departmental initiatives. Beyond academia, he has contributed to industry as Deputy Manager (MIS) at AIAK International, UK, and as Unit Head for Training at Haseen Habib Corporation in Pakistan.

Contributions and Research Focus

Dr. Sattar’s research is anchored in Business Intelligence, Data Analytics, Enterprise Systems, and Information Security. He has secured multiple high-value research grants, including funding from the Pakistan Science Foundation, TWAS-COMSTECH, Malaysia Digital Economy Corporation, and the Malaysia Toray Science Foundation. His contributions extend beyond individual research, encompassing the creation of specialized academic tracks, development of curricula in disruptive technologies, and integration of industrial alliances such as with Microsoft Dynamics, Oracle, SAP, and Coursera.

Impact and Influence

Over two decades, Dr. Sattar has influenced academic landscapes in Pakistan, Malaysia, and the UK. He has mentored students on cutting-edge topics like Generative AI, Industry 4.0, and immersive technologies. As a conference chair, keynote speaker, and session leader, he has shaped dialogues on emerging business technologies. His role as a reviewer for numerous high-impact journals-including Sustainability, Frontiers in Medicine, and ACM Transactions-demonstrates his standing in the scholarly community.

Academic Citations and Recognitions

Dr. Sattar’s scholarly work is recognized through fellowships, travel grants, and the Higher Education Commission’s approval as a Ph.D. supervisor. His funded projects, often exceeding £30,000–£60,000 in value, have advanced applied research in artificial intelligence, data analytics, and enterprise systems. He is regularly invited to deliver talks at international conferences, reflecting the academic community’s acknowledgment of his expertise.

Legacy and Future Contributions

Dr. Sattar’s legacy lies in building academic bridges between industry and education, modernizing curricula, and fostering innovation-driven learning environments. His future trajectory points toward deepening his engagement with AI-driven business intelligence, strengthening global research collaborations, and influencing policy in higher education technology integration. By combining pedagogical innovation with robust research, he continues to prepare students for the demands of a data-driven global economy.

Conclusion

Dr. Mian Usman Sattar’s career exemplifies the synergy between scholarship, industry expertise, and educational leadership. From pioneering business intelligence programs to mentoring the next generation of data scientists, his work reflects both depth and breadth in the evolving field of information systems. His international academic footprint, sustained research output, and leadership roles position him as a transformative figure whose contributions will continue to shape the intersection of technology and business education.

Notable Publications

"Beyond Polarity: Forecasting Consumer Sentiment with Aspect- and Topic-Conditioned Time Series Models

  • Author: Mian Usman Sattar; Raza Hasan; Sellappan Palaniappan; Salman Mahmood; Hamza Wazir Khan
  • Journal: Information
  • Year: 2025

"From promotion to empathy: a content analysis of brand responses to social justice movements

  • Author: Dilshad, W.; Sattar, U.; Ghaffar, A.
  • Journal: Bulletin of Management Review
  • Year: 2025

"Enhancing Supply Chain Management: A Comparative Study of Machine Learning Techniques with Cost–Accuracy and ESG-Based Evaluation for Forecasting and Risk Mitigation

  • Author: Mian Usman Sattar; Vishal Dattana; Raza Hasan; Salman Mahmood; Hamza Wazir Khan; Saqib Hussain
  • Journal: Sustainability
  • Year: 2025

"Exploring the impact of augmented reality on medical students’ intrinsic motivation: a three-dimensional analysis

  • Author: Sattar, U.; Khan, H. W.; Ghaffar, A.; Raza, S.
  • Journal: Journal of Management & Social Science
  • Year: 2025

"Enhancing customer segmentation through factor analysis of mixed data (FAMD)-based approach using K-means and hierarchical clustering algorithms

  • Author: Sattar, U.; Ufeli, C. P.; Hasan, R.; Mahmood, S.
  • Journal: information
  • Year: 2025

Mohammad Reza Nikpour | Artificial Intelligence | Best Researcher Award

Assoc. Prof. Dr. Mohammad Reza Nikpour | Artificial Intelligence | Best Researcher Award

Mohammad Reza Nikpour at University of Mohaghegh Ardabili, Iran📖

Dr. Mohammad Reza Nikpour is an esteemed scholar in Water Engineering, currently serving as a faculty member at the University of Mohaghegh Ardabili, Iran. His expertise lies in hydrodynamics, river engineering, and water resource management, with extensive contributions to computational modeling and environmental sustainability.

Profile

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Education Background🎓

  • Ph.D. in Water Engineering, University of Mohaghegh Ardabili, Iran
  • M.Sc. in Water Engineering, University of Mohaghegh Ardabili, Iran
  • B.Sc. in Water Engineering, University of Mohaghegh Ardabili, Iran

Professional Experience🌱

Dr. Nikpour has been actively involved in academic research and teaching at the University of Mohaghegh Ardabili. His work focuses on computational hydrodynamics, groundwater quality assessment, and flood prediction modeling. He has collaborated with international researchers and contributed to innovative water management solutions through data-driven models.

Research Interests🔬

Her research interests include:

  • Hydrodynamics and River Engineering
  • Groundwater Quality Assessment
  • Soft Computing and AI Applications in Water Resource Management
  • Flood Prediction and Climate Change Impact Studies

Author Metrics

Dr. Mohammad Reza Nikpour has established a strong academic presence with numerous publications in high-impact journals, including River Research and Applications, Journal of Cleaner Production, and Stochastic Environmental Research and Risk Assessment. His research contributions have been widely recognized, earning him a growing citation count on Google Scholar and an impressive h-index on Scopus (to be verified). As a highly cited researcher in water engineering, his work has significantly influenced hydrodynamics, groundwater quality assessment, and computational water resource management. His ORCID ID is 0000-0003-4332-0525, and his research continues to shape innovative solutions in environmental sustainability and AI-driven water system modeling.

Awards and Honors
  • Recognized for outstanding contributions in hydrodynamic modeling and water resource sustainability.
  • Published multiple high-impact research papers in top-tier journals such as River Research and Applications, Journal of Cleaner Production, and Stochastic Environmental Research and Risk Assessment.
  • Recipient of research grants and funding for pioneering studies in environmental and computational water management.
Publications Top Notes 📄

1. Estimation of daily pan evaporation using two different adaptive neuro-fuzzy computing techniques

  • Authors: H. Sanikhani, O. Kisi, M.R. Nikpour, Y. Dinpashoh
  • Journal: Water Resources Management
  • Volume: 26
  • Pages: 4347-4365
  • Year: 2012
  • Citations: 70
  • Summary: This study applies adaptive neuro-fuzzy inference system (ANFIS) models to estimate daily pan evaporation, comparing their accuracy and efficiency in hydrological forecasting.

2. Experimental and numerical simulation of water hammer

  • Authors: M.R. Nikpour, A.H. Nazemi, A.H. Dalir, F. Shoja, P. Varjavand
  • Journal: Arabian Journal for Science and Engineering
  • Volume: 39
  • Pages: 2669-2675
  • Year: 2014
  • Citations: 48
  • Summary: This paper investigates water hammer phenomena using both experimental methods and numerical simulations, providing insights into fluid dynamics and pipeline safety.

3. Exploring the application of soft computing techniques for spatial evaluation of groundwater quality variables

  • Authors: F. Esmaeilbeiki, M.R. Nikpour, V.K. Singh, O. Kisi, P. Sihag, H. Sanikhani
  • Journal: Journal of Cleaner Production
  • Volume: 276
  • Article: 124206
  • Year: 2020
  • Citations: 31
  • Summary: This research explores soft computing techniques, such as machine learning, for the spatial analysis of groundwater quality, enhancing environmental monitoring and sustainability.

4. Hydrodynamics of river-channel confluence: toward modeling separation zone using GEP, MARS, M5 Tree, and DENFIS techniques

  • Authors: O. Kisi, P. Khosravinia, M.R. Nikpour, H. Sanikhani
  • Journal: Stochastic Environmental Research and Risk Assessment
  • Volume: 33 (4-6)
  • Pages: 1089-1107
  • Year: 2019
  • Citations: 28
  • Summary: The study applies various data-driven models, including gene expression programming (GEP) and M5 Tree, to model separation zones in river confluences, improving hydrodynamic predictions.

5. Application of novel data mining algorithms in prediction of discharge and end depth in trapezoidal sections

  • Authors: P. Khosravinia, M.R. Nikpour, O. Kisi, Z.M. Yaseen
  • Journal: Computers and Electronics in Agriculture
  • Volume: 170
  • Article: 105283
  • Year: 2020
  • Citations: 16
  • Summary: This paper investigates the use of advanced data mining techniques to predict discharge and end depth in trapezoidal channels, optimizing water resource management and agricultural planning.

Conclusion

Dr. Mohammad Reza Nikpour is an exceptional researcher in AI-driven water resource management, making him a strong candidate for the Best Researcher Award. His pioneering work in soft computing and AI applications for hydrology and environmental sustainability sets him apart in his field. Expanding into deep learning, increasing industry collaborations, and engaging in AI conferences could further solidify his leadership in AI for water engineering.